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- W2765987089 abstract "Feature selection is the challenging problem in the field of machine learning. The task is to identify the optimal feature subset by eliminating the redundant and irrelevant features from the dataset. The problem becomes more complicated when dealing with high-dimensional datasets. In this paper, we propose the novel technique based on Monte Carlo Tree Search (MCTS) to find the best feature subset to classify the dataset in hand. The effectiveness and validity of the proposed method is demonstrated by experimenting on many real world datasets." @default.
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- W2765987089 date "2017-09-20" @default.
- W2765987089 modified "2023-09-24" @default.
- W2765987089 title "An Effective Feature Selection method using Monte Carlo Search" @default.
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- W2765987089 doi "https://doi.org/10.1145/3129676.3130240" @default.
- W2765987089 hasPublicationYear "2017" @default.
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